Hi everyone – I am really excited to present our paper on an anaesthesia decision support
tool called Cassandra!
My name is Sara Klüber and I present this work on behalf of all my co-authors.
In anesthesia - decision support tools, or DSTs, support the diagnostic process and the
subsequent treatment.
The focus in this paper is on operating room crises in anesthesia that involves both, diagnoses
and treatment.
Typical DSTs for such contexts are, for example, paper-based checklists as you can see on the
current picture.
However, there is a joint issue that many DSTs share.
They fail when implemented in the actual clinical context.
In the case of paper-based checklists, for example, many anesthesiologists forget to
carry them.
We identified some previous work that explored ways to improve the contextual fit on an exploratory
basis, however no theoretical explanation was given on why a certain design succeeded
or failed in the context.
In search for HCI theories that might explain the contextual fit issues we identified theories
of user experience or UX to hold great potential.
Although such theories have been neglected in
safety-critical environments, such as operating
room crises, so far, we hope to convince our listeners and readers that the application
of UX theories is worth considering.
To identify suitable theories in a first step, we compared previous findings on DSTs and
their contextual fit with different UX theories and found two particularly pertinent:
The first one is the theory of psychological need satisfaction that states that good UX
emerges when psychological needs are fulfilled by interacting with a product or service.
As we can see here, the needs for autonomy, competence, and relatedness seem particularly
relevant in the context of DSTs.
For example, previous work described that clinicians feared
that technology might replace their expertise which relates to an unsatisfied or even threatened
need for competence.
Another theory that might explain previous findings is the one of embodiment that states
that a good UX emerges when the interaction with the social and physical environment is
fluent.
Having identified specific theories that might explain previous findings we wanted to further
explore their benefits, especially when designing DSTs.
Therefore, we performed a contextual design process specifically focussing on the psychological
needs and the social and physical environment.
We then evaluated the resulting DST called Cassandra in a simulator-based scenario to
explore its contextual fit.
I will not go into detail concerning the design process of Cassandra, however this slide gives
a quick overview of the different steps.
We started with an immersion into the context and ended with an iterative development of
a wizard of oz prototype subsumed under the term prototyping on this slide.
To get an impression of the final prototype of Cassandra and how it works within the context,
we will have a quick look into a video.
Cassandra needs to be activated by entering a potential diagnosis, for example through
saying “Cassandra show me Sepsis”.
The chosen diagnosis that is based on several symptoms and signs is then displayed no matter
whether plausible to the current situation or not.
Cassandra automatically evaluates symptoms based on the digital data available, however
the anaesthesiologist may re-evaluate and change their status as well.
Symptoms can either be present, green, absent, grey, or undetectable, blue.
The small diagnoses underneath are differential diagnoses sorted by probability.
Anaesthesiologists may consider and select differential diagnosis which prevents them
from fixations.
Since Cassandra is placed above the patient, it is accessible to the entire team and can
serve as a ticket to talk.
To see whether our system would fit into the context of operating room crisis at all, we
decided to preliminarily evaluate it in a simulator-based scenario.
The picture shows the evaluation setup.
Cassandra was tested in 4 teams with at least one anesthetic nurse and one anesthesiologist
as is typical.
Additionally, we integrated two surgeon actors in every trial.
Participants had to handle a simulated emergency case.
Handling the crisis involved diagnosing and treating the simulated patient.
Afterwards, we performed a semi-structured interview concerning the interaction with
Cassandra and its contextual fit.
In the following I will only briefly report on some results but more details may be found
within the paper.
We analyzed the interaction with Cassandra during the scenario from video recordings
using sequence models.
The model on this slide shows the sequence of finding a diagnosis.
It shows that Cassandra was used flexibly at different stages and using different interactions.
For example, Cassandra was used to read symptoms aloud and to confirm them within the team.
Thereby, Cassandra was used to share tasks.
Cassandra seemed to satisfy needs for competence and autonomy as users were provided with the
right information at the right time and could decide on actions to take based upon the information
displayed.
This was well demonstrated with the case of a blue symptom that could only be checked
with a blood-gas-analysis that had to be ordered.
Instead of saying “get a blood-gas-analysis”, Cassandra displayed a symptom and the clinicians
themselves decided to order a blood gas analysis serving their need for autonomy and competence.
Besides the interactions we also analyzed the interviews that brought to the fore interesting
insights concerning UX theories.
For example, one participant said: “The decision-making process can´t be taken
away from the anesthesiologists.
The system narrows down possibilities, and maybe you discover something that you didn´t
consider before, but the decision in which direction you want to go is not taken away
by the system.
I wouldn´t like it if it did [take the decision away]”
This statement clearly highlights Cassandras ability to satisfy the need for autonomy and
competence and how this satisfaction lead to the acceptance of Cassandra.
And another participant expressed Cassandra’s ability to support social coupling as follows:
“you can use it as a communication tool that everyone knows what is going on […]
I'm currently missing such a possibility, to
be honest”
This slide summarizes some of our key design suggestions for DST designs that are based
on the insights gained from our focus on UX theories during design and evaluation.
For example, Cassandra was able to satisfy needs for autonomy by leaving decisions to
the user and by giving users the final say.
This subsequently lead to the acceptance of the
system and to a fit into the context.
Our work has several limitations.
First, our sample size in both contextual inquiry and evaluation were rather small and
results depend on the chosen sample.
Second, we did not evaluate a UX-driven versus a non-ux-driven design which we aim to perform
in future work.
Third, we tested our system in a simulated environment and in a single scenario rather
than long-term and in the real clinical context.
Overall, we argue that a needs-based and embodied UX perspective suit the design of DSTs for
the clinical context.
The theories chosen were able to theoretically explain previous findings and they aided in
gaining new insights into the design and use of DSTs in anesthesia.
We think that the UX perspective might even contribute to DST design beyond the clinical
context and argue that we should continue to apply UX theories to context of safety-critical
environments as well.
Thanks for listening! :)